search for: rvmmin

Hi, Mark et al.: Thanks, Mark. Three comments: 1. Rvmmin was one of the methods I tried after Ravi directed me to optimx. It returned NAs for essentially everything. See my email of this subject stamped 4:43 PM Central time = 21:43 UTC. 2. It would be interesting to know if the current algorithm behind optim and optimx with method=...

Hello: The development version of Ecdat on R-Forge contains a vignette in which optim(?, method=?L-BFGS-B?) stops with an error message while violating the lower bound. To see all the details, try the following: install.packages("Ecdat", repos="http://R-Forge.R-project.org") Then do "help(pac=Ecdat)" -> "User guides, package

Hi Spencer: See the link below about L-BFGS-B below because I had problems with it a good while back (and I think the link description is the cause but I can't prove it ) so eventually I moved to the Rvmmin(b) package. It's a package but really an algorithm. Rvmmin(b) uses a variable-metric algorithm similar to that of L-BFGS-B but without the problem below. It's not surprisingly a creation of John Nash and quite impressive based on my experience. Just like L-BFGS, it can implement box constra...

...information: package 'numDeriv' successfully unpacked and MD5 sums checked package 'BB' successfully unpacked and MD5 sums checked package 'ucminf' successfully unpacked and MD5 sums checked package 'Rcgmin' successfully unpacked and MD5 sums checked package 'Rvmmin' successfully unpacked and MD5 sums checked package 'minqa' successfully unpacked and MD5 sums checked package 'setRNG' successfully unpacked and MD5 sums checked package 'optimx' successfully unpacked and MD5 sums checked The downloaded packages are in C:\Documents...

...Theussl and others have the R Optimization Infrastructure. There are some differences of focus in these projects. For the present poster, I cannot unfortunately help much on GNLM details, but I can say that there are trial versions of methods that will handle bounds (packages minqa, Rcgmin and Rvmmin) that accept bounds, along with existing L-BFGS-B in optim(). Rcgmin and Rvmmin also accept "masks", that is fixed parameters. These routines are about to go into CRAN. It appears GNLM is not a CRAN package. Does it permit substitution of optimizer? That is something those of us workin...

Hi, I would like to write a function that finds parameters of a log-normal distribution with a 1-alpha CI of (x_lcl, x_ucl): However, I don't know how to optimize for the two unknown parameters. Here is my unsuccessful attempt to find a lognormal distribution with a 90%CI of 1,20: prior <- function(x_lcl, x_ucl, alpha, mean, var) { a <- (plnorm(x_lcl, mean, var) - (alpha/2))^2 b

Hi, Currently I am trying to solve a minimization problem using optim as method Nelder-Mead. However, Neldel-Mead needs many iterations until it finally converges. I have set $control.trace and $control.report such that I can see the value of the function at each iteration. I do see that I set the convergence criteria to strict in the sense that the function value does not change much. However,

...bably will do so in a later version after we figure out what advice to give on where it is appropriate to apply it. In the meantime, I would suggest that BFGS or L-BFGS-B are the closest options in optim() and generally perform quite well. There are updates to BFGS and CG on CRAN in the form of Rvmmin and Rcgmin which are all-R implementations with box constraints too. UCMINF is a very similar implementation of the unconstrained algorithm that seems to have the details done rather well -- though BFGS in optim() is based on my work, I actually find UCMINF often does better. There's also nl...

Hello! I am trying to create an R optimization routine for a task that's currently being done using Excel (lots of tables, formulas, and Solver). However, otpim seems to be finding a local minimum. Example data, functions, and comparison with the solution found in Excel are below. I am not experienced in optimizations so thanks a lot for your advice! Dimitri ### 2 Inputs:

...reserve the name. The real package is optimrx on R-forge (dependencies can fail, then the poor maintainer gets "your package doesn't work", with no hope of fixing it). Moreover, Harry Joe recently pointed out to me a bug and in the last few weeks I think I've resolved issues where Rvmmin and other packages got NA results when numerical gradient approximations were used in certain ways. optimrx came about because I realized that optimx() has just enough difference in syntax from optim() to be a nuisance and was heavy to maintain. Also I wanted parameter scaling to work for all meth...

Dear R Help, I have two nested negative log-likelihood functions that I am optimizing with the spg function [BB package]. I would like to perform model selection on these two objective functions using AIC (and possibly anova() too). However, the spg() function returns a list and I need a fitted model object for AIC(), ICtab() [bbmle package], or anova(). How can I perform AIC-based model

Hey, R users I do not know how to describe my question. I am a new user for R and write the following?code for a dynamic labor economics?model and use OPTIM to get optimizations and parameter values. the following code does not work due to the?equation: ?? wden[,i]<-dnorm((1-regw[,i])/w[5])/w[5] where w[5]?is one of the parameters (together with vector a, b and other elements in vector

Rob J Hyndman gives great explanation here (https://robjhyndman.com/hyndsight/estimation/) for reasons why results from R's arima may differ from other softwares. @iacobus, to cite one, 'Major discrepancies between R and Stata for ARIMA' (https://stackoverflow.com/questions/22443395/major-discrepancies-between-r-and-stata-for-arima), assign the, sometimes, big diferences from R

Hi R users, I am trying to restrct the range of two of the parameters in a maximization problem. Both parameters should be between -1 and 1. As far as I know, if I choose the estimation method ="L-BFGS-B" under Optim, I can restrict the parameter space. However, the "L-BFGS-B" always require finite values of the loglik function and cannot get around of the problem if an

I'm using nls to fit a variety of different models. Here I use SSgompertz as an example. I want the ability to fix one (or more) of the coefficients that would normally be optimised (e.g. fix b3=0.8). Examples; based on and using data from example(SSgompertz) #--------------------- # vanilla call to nls, no coefficients fixed, works fine nls(density ~ SSgompertz(log(conc), Asym, b2, b3),

...Nelder-Mead, CG, and BFGS in optim() in the mid 1970s. CG never did as well as I would like, but the other two routines turned out pretty well. However, in nearly 40 years, there are a few improvements, particularly in handling bounds and masks (fixed parameters). For all-R routines see Rcgmin and Rvmmin. Rather than directly use the optim() routines in C, you may want to use some more modern ones, but the choice may be dependent on your problem. JN On 06/09/2012 06:00 AM, r-devel-request at r-project.org wrote: > Message: 2 > Date: Fri, 8 Jun 2012 09:40:17 -0400 > From: Edward Worbis &l...

While lm() is a linear modeling, the constraints make it easier to solve with a nonlinear tool. Both my packages Rvmmin and Rcgmin (I recommend the R-forge versions as more up-to-date) have bounds constraints and "masks" i.e., fixed parameters. I am actually looking for example problems of this type that are more recent than the ones that got me into this 30 years ago. Do contact me off-list if you have s...

...ers. It surprises me that it doesn't happen much more frequently. The "BFGS" method of optim() from the 1990 Pascal version of my book was called the Variable Metric method as per Fletcher's 1970 paper it was drawn from. It really works much better with analytic gradients, and the Rvmmin package which is an all-R version that adds bounds and masks is set up to generate a warning if they are not available. Even with bounds, the finite different derivative code can step over a cliff edge with del <- (f(x+h) - f(x))/h i.e., bounds may not be checked within the numerical derivati...

Hi. I just noticed the paper by Morales and Nocedal Remark on "Algorithm 778: L-BFGS-B: Fortran Subroutines for Large-Scale Bound Constrained Optimization". TOMS 2011; 38(1): 7 http://www.ece.northwestern.edu/~morales/PSfiles/acm-remark.pdf which describes a couple of improvements (speed and accuracy) to the original Netlib code which AFAICT is that still used by optim() via f2c.

Hi, I'm using optim with box constraints to MLE on about 100 data points. It goes quite slow even on 4GB machine. I'm wondering if R has any faster implementation? Also, if I'd like to impose equality/nonequality constraints on parameters, which package I should use? Any help would be appreciated. Thank you. rc